Tag: price volatility

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Who Tweets Wins

Today’s title is inspired from the British Special Air Service (SAS) famous catchphrase, ‘Who Dares Wins’ – similar variations of which have been adopted by several elite army units around the world. The motto is often credited to the founder of the SAS, Sir David Stirling (although similar phrases can be traced back to ancient Rome – including ‘qui audet adipiscitur’, which is Latin for ‘who dares wins’). The motto was used to inspire and remind soldiers that to successfully accomplish difficult missions, one has to take risks (Geraghty, 1980).

In the world of economics and finance, the concept of risk is endemic to investments and to making decisions in an uncertain world. The ‘no free lunch’ principle in finance, for instance, asserts that it is not possible to achieve exceptional returns over the long term without accepting substantial risk (Schachermayer, 2008).

Undoubtedly, one of the riskiest investment instruments you can currently get your hands on is cryptocurrencies. The most well-known of them is Bitcoin (BTC), and its price has varied spectacularly over the past ten years – more than any other asset I have laid my eyes on in my lifetime.

The first published exchange rate of BTC against the US dollar dates back to 5 October 2009 and it shows $1 to be exchangeable for 1309.03 BTC. On 15 December 2017, 1 BTC was traded for $17,900. But then, a year later the exchange rate was down to just over $1 = $3,500. Now, if this is not volatility I don’t know what is!

In such a market, wouldn’t it be wonderful if you could somehow predict changes in market sentiment and volatility trends? In a hot-off-the press article, Shen et al (2019) assert that it may be possible to predict changes in trading volumes and realised volatility of BTC by using the number of BTC-related tweets as a measure of attention. The authors source Twitter data on Bitcoin from BitInfoCharts.com and tick data from Bitstamp, one of the most popular and liquid BTC exchanges, over the period 4/9/2014 to 31/8/2018.

According to the authors:

This measure of investor attention should be more informed than that of Google Trends and therefore may reflect the attention Bitcoin is receiving from more informed investors. We find that the volume of tweets are significant drivers of realised [price] volatility (RV) and trading volume, which is supported by linear and nonlinear Granger causality tests.

They find that, according to Granger causality tests, for the period from 4/9/2014 to 8/10/2017, past days’ tweeting activity influences (or at least forecasts) trading volume. While from 9/10/2017 to 31/8/2018, previous tweets are significant drivers/forecasters of not only trading volume but also realised price volatility.

And before you reach out for your smartphone, let me clarify that, although previous days’ tweets are found in this paper to be good predictors of realised price volatility and trading volume, they have no significant effect on the returns of Bitcoin.

Article

References

Questions

  1. Explain how the number of tweets can be used to gauge investors’ intentions and how it can be linked to changes in trading volume.
  2. Using Google Scholar, make a list of articles that have used Twitter and Google Trends to predict returns, volatility and trading volume in financial markets. Present and discuss your findings.
  3. Would you invest in Bitcoin? Why yes? Why no?
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Lobster for all?

Over the past few years lobster prices in Maine have tumbled. Eight years ago the price paid to fishermen was around $4.60 per pound. Today it’s around $2.20. The problem is one of booming lobster populations and the dominance of lobster in catches. Last year’s haul was double that of a decade ago and, in some waters, six times higher.

You would think that larger catches would be good news for fishermen. But prices now are so low that they barely cover variable costs. Individual fishermen fish harder and longer to bring in even bigger catches to make up for the lower price. This, of course, compounds the problem and pushes the price even lower.

So what are the answers for the fishermen of Maine? One solution is to diversify their catch, but with lobster so plentiful and other fish stocks depleted, this is not easy.

Another solution is to cooperate. The Reuters article below quotes John Jordan, a lobsterman and president of Calendar Islands Maine Lobster Co.:

‘If you had an industry that actually cooperated, you wouldn’t be bringing in more product if you couldn’t sell what you already had, right?’

Restricting the catch would require lobster distributors to cooperate and set quotas for what the fishermen would be permitted to sell. But with over 5000 fishermen, this is not easy.

Another solution is to expand the market. One way is for the distributors or other agencies to market lobster and lobster products more aggressively. For example, this year the State of Maine has established a $2 million marketing collaborative. Another solution is to find new markets.

Jordan’s company and others are frantically seeking new ways to sneak lobster into unexpected corners of the food market, from gazpacho to puff pastries and quiche.

In the meantime, for consumers the question is whether the low prices paid to the fishermen of Maine will feed through into low prices in the fishmonger, supermarket and restaurant. So far that does not seem to be happening, as the final two articles below explain.

Webcasts

US lobster fishermen’s ‘problem of plenty’ BBC News, Jonny Dymond (5/10/13)
Maine lobstermen in a pinch over low prices, record catch: Part 1, Part 2, Part 3 Aljazeera America, Adam May (11/10/13)

Articles

Something fishy is going on in the nation’s lobster capital CNBC, Heesun Wee (1/9/13)
Booming lobster population pinches profits for Maine’s fishery Reuters, Dave Sherwood (25/8/13)
Lobster’s worth shelling out for The Observer,
Rachel Cooke (21/9/13)
Clawback The New Yorker, James Surowiecki (26/8/13)
Why The Glut Of Cheap Lobster Won’t Lower Price Of Lobster Rolls Gothamist, John Del Signore (20/7/12)

Questions

  1. Why have lobster prices paid to fishermen fallen? Illustrate your argument with a demand and supply diagram
  2. What has determined the size of the fall in prices? What is the relevance of price elasticity of demand and price elasticity of supply to your answer?
  3. How is the fallacy of composition relevant to the effects on profits of an increase in the catch by (a) just one fisherman and (b) all fishermen? What incentive does this create for individual fishermen in a competitive market?
  4. What can lobster fishermen do to restore profit margins through collaborative action?
  5. In what ways is there a conflict between economics and ecology in the lobster fishing industry?
  6. How does stored lobster affect (a) the price elasticity of supply and (b) the price volatility of lobster?
  7. How could cooperation between lobster fishermen and lobster processors and distributors benefit all those involved in the cooperation?
  8. Why may restaurants choose to maintain high prices for lobster dishes for ‘psychological reasons’? Are there any other reasons?